Cognitive balancing IT ecosystems

Abstract

An approach is provided in which an information handling system loads a set of event data corresponding to an information technology (IT) ecosystem into a blockchain framework. The blockchain framework, in turn, generates a set of anomaly data based on the set of event data. The information handling system identifies a set of parameter values to adjust corresponding to the IT ecosystem based on the set of anomaly data, and the information handling system then optimizes the IT ecosystem by adjusting the identified set of parameter values in the IT ecosystem.

Description

BACKGROUND[0001]New technologies are making business more intelligent, fast and scalable. As the world becomes more connected, organizations encounter increasingly difficulty competing as solo entities. In today's era of exponentially increasing data and information, and ubiquitous digitization, a new economic equation favors transparency and collaboration between businesses.[0002]In search of innovation, businesses are opening up their enterprises and removing barriers to extend collaboration both inside and outside their organizations. As a result, the focus of innovation is shifting from organization-centric to one that is ecosystem-centric. An ecosystem can be thought of as a complex web of interdependent enterprises and relationships that creates and allocates business value. Ecosystems are broad by nature, potentially spanning multiple geographies and industries, including public and private institutions and consumers.[0003]Along those lines, information technology (IT) ecosys...

AI Technical Summary

Benefits of technology

The solution enables continuous optimization and balancing of IT ecosystems, reducing dependence on skilled staff and improving adaptability to changes, ensuring optimal business outcomes by leveraging blockchain-generated anomaly data for parameter adjustments.

Problems solved by technology

As the world becomes more connected, organizations encounter increasingly difficulty competing as solo entities.

Challenges found with this approach include slow and cumbersome adaptation to change in the IT ecosystem when recoding / reconfiguring the existing management systems.

Another challenge found is that the operational quality and success of evolving the IT ecosystem is closely aligned to the skills and experience of the staff / consultants owning / running the balancing & optimization processes.

In short, the more complex an IT ecosystem, the less likely the IT ecosystem is successfully managed to achieve an optimal balance of desired business outcomes.

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